Detect irregularly shaped spatio-temporal clusters for decision support
Many real-world applications call for the use of detecting unusual clusters (abnormal phenomena or significant change) from spatio-temporal data for decision support, e.g., in disease surveillance systems and crime monitoring systems. More accurate detection can offer stronger decision support to enable more effective early warning and efficient resource allocation. Many spatial/spatio-temporal clustering approaches have been designed to detect significantly unusual clusters for decision...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics, SOLI 2011|
|01_Dong_Detect_irregularly_shaped_2011.pdf||724.19 kB||Adobe PDF||Request a copy|
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